{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 可视化决策树的方式"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-04-17T06:53:16.712193Z",
     "start_time": "2022-04-17T06:53:16.682306Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DecisionTreeClassifier(max_depth=3, random_state=42)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.datasets import load_iris\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn import tree\n",
    "import graphviz\n",
    "# 加载数据集\n",
    "dataset = load_iris() \n",
    "# 转换成.DataFrame形式\n",
    "df = pd.DataFrame(dataset.data, columns = dataset.feature_names)\n",
    "# 添加品种列\n",
    "df['Species'] = dataset.target\n",
    "\n",
    "# 用数值替代品种名作为标签\n",
    "target = np.unique(dataset.target)\n",
    "target_names = np.unique(dataset.target_names)\n",
    "targets = dict(zip(target, target_names))\n",
    "df['Species'] = df['Species'].replace(targets)\n",
    "\n",
    "# 提取数据和标签\n",
    "X = df.drop(columns=\"Species\")\n",
    "y = df[\"Species\"]\n",
    "feature_names = X.columns\n",
    "labels = y.unique()\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X,y,\n",
    "                                                 test_size = 0.4,\n",
    "                                                 random_state = 42)\n",
    "model = DecisionTreeClassifier(max_depth =3, random_state = 42)\n",
    "model.fit(X_train, y_train)                                         "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 文字表示"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-04-17T05:19:31.659736Z",
     "start_time": "2022-04-17T05:19:31.649787Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "|--- feature_2 <= 2.45\n",
      "|   |--- class: setosa\n",
      "|--- feature_2 >  2.45\n",
      "|   |--- feature_3 <= 1.75\n",
      "|   |   |--- feature_2 <= 5.35\n",
      "|   |   |   |--- class: versicolor\n",
      "|   |   |--- feature_2 >  5.35\n",
      "|   |   |   |--- class: virginica\n",
      "|   |--- feature_3 >  1.75\n",
      "|   |   |--- feature_2 <= 4.85\n",
      "|   |   |   |--- class: virginica\n",
      "|   |   |--- feature_2 >  4.85\n",
      "|   |   |   |--- class: virginica\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# 以文字形式输出树     \n",
    "text_representation = tree.export_text(model)\n",
    "print(text_representation)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### plot_tree函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-04-17T05:20:47.302004Z",
     "start_time": "2022-04-17T05:20:46.544367Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2160x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 用图片画出\n",
    "plt.figure(figsize=(30,10), facecolor ='g') #\n",
    "a = tree.plot_tree(model,\n",
    "                   feature_names = feature_names,\n",
    "                   class_names = labels,\n",
    "                   rounded = True,\n",
    "                   filled = True,\n",
    "                   fontsize=14)\n",
    "plt.show()  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### graphviz模块\n",
    "\n",
    "该模块需要安装graphviz，推荐在ubuntu上```sudo apt install graphviz```或者Mac上```brew install graphviz```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-04-17T05:59:24.350899Z",
     "start_time": "2022-04-17T05:59:23.902059Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/svg+xml": [
       "<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\"?>\r\n",
       "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\r\n",
       " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\r\n",
       "<!-- Generated by graphviz version 2.50.0 (20211204.2007)\r\n",
       " -->\r\n",
       "<!-- Title: Tree Pages: 1 -->\r\n",
       "<svg width=\"530pt\" height=\"433pt\"\r\n",
       " viewBox=\"0.00 0.00 530.00 433.00\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\r\n",
       "<g id=\"graph0\" class=\"graph\" transform=\"scale(1 1) rotate(0) translate(4 429)\">\r\n",
       "<title>Tree</title>\r\n",
       "<polygon fill=\"white\" stroke=\"transparent\" points=\"-4,4 -4,-429 526,-429 526,4 -4,4\"/>\r\n",
       "<!-- 0 -->\r\n",
       "<g id=\"node1\" class=\"node\">\r\n",
       "<title>0</title>\r\n",
       "<polygon fill=\"#fdfcff\" stroke=\"black\" points=\"266,-425 108,-425 108,-342 266,-342 266,-425\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"187\" y=\"-409.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">petal length (cm) &lt;= 2.45</text>\r\n",
       "<text text-anchor=\"middle\" x=\"187\" y=\"-394.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">gini = 0.665</text>\r\n",
       "<text text-anchor=\"middle\" x=\"187\" y=\"-379.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 90</text>\r\n",
       "<text text-anchor=\"middle\" x=\"187\" y=\"-364.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [27, 31, 32]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"187\" y=\"-349.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = virginica</text>\r\n",
       "</g>\r\n",
       "<!-- 1 -->\r\n",
       "<g id=\"node2\" class=\"node\">\r\n",
       "<title>1</title>\r\n",
       "<polygon fill=\"#e58139\" stroke=\"black\" points=\"167,-298.5 55,-298.5 55,-230.5 167,-230.5 167,-298.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"111\" y=\"-283.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">gini = 0.0</text>\r\n",
       "<text text-anchor=\"middle\" x=\"111\" y=\"-268.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 27</text>\r\n",
       "<text text-anchor=\"middle\" x=\"111\" y=\"-253.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [27, 0, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"111\" y=\"-238.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = setosa</text>\r\n",
       "</g>\r\n",
       "<!-- 0&#45;&gt;1 -->\r\n",
       "<g id=\"edge1\" class=\"edge\">\r\n",
       "<title>0&#45;&gt;1</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M160.63,-341.91C153.32,-330.65 145.37,-318.42 138.03,-307.11\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"140.93,-305.15 132.54,-298.67 135.06,-308.96 140.93,-305.15\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"127.35\" y=\"-319.42\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">True</text>\r\n",
       "</g>\r\n",
       "<!-- 2 -->\r\n",
       "<g id=\"node3\" class=\"node\">\r\n",
       "<title>2</title>\r\n",
       "<polygon fill=\"#fbf9fe\" stroke=\"black\" points=\"340.5,-306 185.5,-306 185.5,-223 340.5,-223 340.5,-306\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"263\" y=\"-290.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">petal width (cm) &lt;= 1.75</text>\r\n",
       "<text text-anchor=\"middle\" x=\"263\" y=\"-275.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">gini = 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"263\" y=\"-260.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 63</text>\r\n",
       "<text text-anchor=\"middle\" x=\"263\" y=\"-245.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [0, 31, 32]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"263\" y=\"-230.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = virginica</text>\r\n",
       "</g>\r\n",
       "<!-- 0&#45;&gt;2 -->\r\n",
       "<g id=\"edge2\" class=\"edge\">\r\n",
       "<title>0&#45;&gt;2</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M213.37,-341.91C219.09,-333.1 225.19,-323.7 231.1,-314.61\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"234.17,-316.31 236.68,-306.02 228.3,-312.5 234.17,-316.31\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"241.87\" y=\"-326.78\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">False</text>\r\n",
       "</g>\r\n",
       "<!-- 3 -->\r\n",
       "<g id=\"node4\" class=\"node\">\r\n",
       "<title>3</title>\r\n",
       "<polygon fill=\"#53e892\" stroke=\"black\" points=\"254,-187 96,-187 96,-104 254,-104 254,-187\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"175\" y=\"-171.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">petal length (cm) &lt;= 5.35</text>\r\n",
       "<text text-anchor=\"middle\" x=\"175\" y=\"-156.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">gini = 0.208</text>\r\n",
       "<text text-anchor=\"middle\" x=\"175\" y=\"-141.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 34</text>\r\n",
       "<text text-anchor=\"middle\" x=\"175\" y=\"-126.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [0, 30, 4]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"175\" y=\"-111.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = versicolor</text>\r\n",
       "</g>\r\n",
       "<!-- 2&#45;&gt;3 -->\r\n",
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       "<graphviz.files.Source at 0x21300e9a2e0>"
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     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "dot_data = tree.export_graphviz(model, out_file=None, \n",
    "                                feature_names=dataset.feature_names,  \n",
    "                                class_names=dataset.target_names,\n",
    "                                filled=True)\n",
    "\n",
    "# Draw graph\n",
    "graph = graphviz.Source(dot_data, format=\"png\") \n",
    "graph"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### dtreeviz模块"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-04-17T06:47:56.761864Z",
     "start_time": "2022-04-17T06:47:56.573559Z"
    }
   },
   "outputs": [],
   "source": [
    "dtreeviz??"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-04-17T06:51:10.914252Z",
     "start_time": "2022-04-17T06:51:10.020624Z"
    }
   },
   "outputs": [
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     "name": "stderr",
     "output_type": "stream",
     "text": [
      "E:\\python-tool\\Anaconda\\lib\\site-packages\\numpy\\core\\_asarray.py:83: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray\n",
      "  return array(a, dtype, copy=False, order=order)\n"
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      ],
      "text/plain": [
       "<dtreeviz.trees.DTreeViz at 0x21301951820>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from dtreeviz.trees import *\n",
    "\n",
    "# 准备数据\n",
    "X = dataset.data\n",
    "y = dataset.target\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
    "\n",
    "# 拟合\n",
    "clf = tree.DecisionTreeClassifier(max_depth=3, random_state=42)\n",
    "clf.fit(X_train, y_train)\n",
    "\n",
    "viz = dtreeviz(clf, \n",
    "               x_data=X_train,\n",
    "               y_data=y_train,\n",
    "               target_name='class',\n",
    "               feature_names=dataset.feature_names, \n",
    "               class_names=list(dataset.target_names), \n",
    "               title=\"Decision Tree - Iris data set\")\n",
    "viz"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## sns.heatmap可视化报告"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-04-17T06:54:07.029970Z",
     "start_time": "2022-04-17T06:54:06.849400Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "      setosa       1.00      1.00      1.00        23\n",
      "  versicolor       0.95      1.00      0.97        19\n",
      "   virginica       1.00      0.94      0.97        18\n",
      "\n",
      "    accuracy                           0.98        60\n",
      "   macro avg       0.98      0.98      0.98        60\n",
      "weighted avg       0.98      0.98      0.98        60\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.metrics import classification_report\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "y_pred = model.predict(X_test)\n",
    "target_names = np.unique(dataset.target_names)\n",
    "clf_report = classification_report(y_test,\n",
    "                                   y_pred,\n",
    "                                   labels=labels,\n",
    "                                   target_names=target_names)\n",
    "print(clf_report)\n",
    "clf_report = classification_report(y_test,\n",
    "                                   y_pred,\n",
    "                                   labels=labels,\n",
    "                                   target_names=target_names,\n",
    "                                   output_dict=True)\n",
    "plt.figure(figsize=(8,6))\n",
    "sns.heatmap(pd.DataFrame(clf_report).iloc[:-1, :].T, annot=True)\n",
    "plt.show()"
   ]
  }
 ],
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